Simulation of forest tree species' bud burst dates for different climate scenarios: chilling requirements and photo-period may limit bud burst advancement

Warming Events Advance or Delay Spring Phenology by Affecting Bud Dormancy Depth in Trees

The frequency of sudden, strong warming events is projected to increase in the future. The effects of such events on spring phenology of trees might depend on their timing because spring warming has generally been shown to advance spring budburst while fall and winter warming have been shown to delay spring phenology. To understand the mechanism behind timing-specific warming effects on spring phenology, I simulated warming events during fall, mid-winter and at the end of winter and quantified their effects on bud dormancy depth and subsequently on spring leaf out. The warming events were carried out in climate chambers on tree seedlings of Betula pendula and Fagus sylvatica in October, January, and February. Control seedlings were kept at photoperiod and temperature matching the daily fluctuating field conditions. Warmed seedlings were kept 10°C warmer than the control seedlings for 10 days during the respective warming periods. Warming in October increased bud dormancy depth and decreased spring leaf-out rate only for F. sylvatica, whereas warming in February reduced bud dormancy depth and advanced spring leaf-out rate only for B. pendula. Neither bud dormancy depth nor spring leaf out rate were affected by January warming. The results indicate that warming-induced changes in bud dormancy depth may explain species- and timing-specific warming effects on spring phenology. The extent to which the timing of bud dormancy phases is species-specific will influence among-species variation in future spring leaf out times.

A novel sunshine duration-based photothermal time model interprets the photosensitivity of flower maturity of pecan cultivars

Although it is well-known and established that light plays important roles in plant development, up to now, there is no substantial improvements in how to deal with the light factor of spring phenology under natural condition. By monitoring the local meteorologic data and mature dates of two types (male and female) of flower from four pecan cultivars during 9 years, it was found that the complementary pattern of growing degree day and sunshine duration helped to maintain a threshold of driving force related to the maturity of pecan flower during 9 years. A novel photothermal time model based on the linear combination of growing degree day and sunshine duration was then proposed and validated to interpret the variance of mature dates of pecan cultivars. Comparative analysis showed that the new model had made extremely significant improvements to the traditional thermal time model. In addition, this model introduced the conversion coefficient K, which quantified the effect of light on the flowering drive, and revealed the differences of base temperature among cultivars. This was the first time that sunshine duration instead of photoperiod was adopted to develop into a verified model on spring phenological event of tree species. It will help to model the spring phenologies of other tree species more reasonably.

Projections for the changes in growing season length of tree-ring formation on the Tibetan Plateau based on CMIP5 model simulations

The response of the growing season to the ongoing global warming has gained considerable attention. In particular, how and to which extent the growing season will change during this century is essential information for the Tibetan Plateau, where the observed warming trend has exceeded the global mean. In this study, the 1960-2014 mean length of the tree-ring growing season (LOS) on the Tibetan Plateau was derived from results of the Vaganov-Shashkin oscilloscope tree growth model, based on 20 composite study sites and more than 3000 trees. Bootstrap and partial correlations were used to evaluate the most significant climate factors determining the LOS in the study region. Based on this relationship, we predicted the future variability of the LOS under three emission scenarios (Representative Concentration Pathways (RCP) 2.6, 6.0, and 8.5, representing different concentrations of greenhouse gasses) derived from 17 Earth system models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5). The averaged LOS on the Tibetan Plateau is 103 days during the period 1960-2014, and April-September minimum temperature is the strongest factor controlling the LOS. We detected a general increase in the LOS over the twenty-first century under all the three selected scenarios. By the middle of this century, LOS will extend by about 3 to 4 weeks under the RCPs 2.6 and 6.0, and by more than 1 month (37 days) under the RCP 8.5, relative to the baseline period 1960-2014. From the middle to the end of the twenty-first century, LOS will further extend by about 3 to 4 weeks under the RCPs 6.0 and 8.5, respectively. Under the RCP 2.6 scenario, however, the extension reaches a plateau at around 2050 and about 2 weeks LOS extension. In total, we found an average rate of 2.1, 3.6, and 5.0 days decade^-1 for the LOS extension from 2015 to 2100 under the RCPs 2.6, 6.0, and 8.5, respectively. However, such estimated LOS extensions may be offset by other ecological factors that were not included into the growth model. The estimated lengthening of the growing season could substantially affect carbon sequestration and forest productivity on the Tibetan Plateau.

Using Multitemporal Sentinel-1 C-band Backscatter to Monitor Phenology and Classify Deciduous and Coniferous Forests in Northern Switzerland

Efficient methods to monitor forested areas help us to better understand their processes. To date, only a few studies have assessed the usability of multitemporal synthetic aperture radar (SAR) datasets in this context. Here we present an analysis of an unprecedented set of C-band observations of mixed temperate forests. We demonstrate the potential of using multitemporal C-band VV and VH polarisation data for monitoring phenology and classifying forests in northern Switzerland. Each SAR acquisition was first radiometrically terrain corrected using digital elevation model-based image simulations of the local illuminated area. The flattened backscatter values and the local area values were input to a temporal compositing process integrating backscatter values from ascending and descending tracks. The process used local resolution weighting of each input, producing composite backscatter values that strongly mitigated terrain-induced distortions. Several descriptors were calculated to show the seasonal variation of European beech (Fagus sylvatica), oak (Quercus robur, Quercus petraea) and Norway spruce (Picea abies) in C-band data. Using their distinct seasonal signatures, the timing of leaf emergence and leaf fall of the deciduous species were estimated and compared to available ground observations. Furthermore, classifications for the forest types ‘deciduous’ and ‘coniferous’ and the investigated species were implemented using random forest classifiers. The deciduous species backscatter was about 1 dB higher than spruce throughout the year in both polarisations. The forest types showed opposing seasonal backscatter behaviours. At VH, deciduous species showed higher backscatter in winter than in summer, whereas spruce showed higher backscatter in summer than in winter. In VV, this pattern was similar for spruce, while no distinct seasonal behaviour was apparent for the deciduous species. The time differences between the estimations and the ground observations of the phenological events were approximately within the error margin ( ± 12 days) of the temporal resolution. The classification performances were promising, with higher accuracies achieved for the forest types (OA of 86% and κ = 0.73) than for individual species (OA of 72% and κ = 0.58). These results show that multitemporal C-band backscatter data have significant potential to supplement optical remote sensing data for ecological studies and mapping of mixed temperate forests.

Validating MODIS and Sentinel-2 NDVI Products at a Temperate Deciduous Forest Site Using Two Independent Ground-Based Sensors

Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS). The influence of different spatial and temporal resolutions was assessed. High correlations and similar phenological patterns between in situ and satellite-based NDVI time series demonstrated the reliability of satellite-based phenological metrics. Sentinel-2-derived metrics showed better agreement with in situ measurements than MODIS-derived metrics. Dynamic filtering with the best index slope extraction algorithm was nevertheless beneficial for Sentinel-2 NDVI time series despite the availability of quality information from the atmospheric correction procedure.